Geospatial analysis

Consulting on Methodology & Research Questionnaire Design.

Data Collection & Processing.

Statistical Data Analysis Across Several Techniques.

Geospatial analysis is the gathering, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly, in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

The many applications of geospatial analysis include crisis management, climate change modeling, weather monitoring, sales analysis, human population forecasting and animal population management.

Geospatial analyst filter out relevant from irrelevant data and apply it to conceptualize and visualize the order hidden within the apparent disorder of geographically sorted data. Doing so allows them to provide accurate trend analysis, modeling and predictions. However, analysts must remain vigilant to try to avoid spatial fallacies, biases or misunderstanding effects and causal relationships: Geospatial analysis is sometimes considered to encompass as much intuition as it does science.


Cassandra database is used to handle the large set of data when we need to scale the database with high performance. Cassandra deals with the fault tolerance and replication of the data. With this we can go deeper in columns, supercolumns and more. It is a partial relational database system, supports best query capability but don’t have joins feature. It follows the column family model map with two dimensional and 3 dimensional. 2D model includes column family with some column in it, while 3D model created by associating super column in column family.

MongoDB is an agile NoSQL document database, unlike the traditional database which store the data in rows and column, MongoDB stores the document data in binary form of JSON document which is also known as BSON format. It is used for high scalability, availability and performance. In MongoDB dynamic schemas are the unit of database, which found in document where set of documents are found in collection while set of collection makes the database.

Pentaho Kettle Pentaho Data Integration (PDI, also called Kettle) is the component of Pentaho responsible for the Extract, Transform and Load (ETL) processes. Though ETL tools are most frequently used in data warehouses environments, PDI can also be used for other purposes: Migrating data between applications or databases.

Saiku Business Analytics allows business users to explore complex data sources, using a familiar drag and drop interface and easy to understand business terminology, all within a browser. Select the data you are interested in, look at it from different perspectives, drill into the detail. Once you have your answer, save your results, share them, export them to Excel or PDF, all straight from the browser.

Node.js is a platform built on Chrome's JavaScript runtime for easily building fast and scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.

R  is an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.

MACHINE CODE GeoSpatial Analytics team gives you access to resources capable of guiding you through the entire research lifecycle, from developing a methodology to delivering the results that delight your clients. This allows you to gain efficiencies, and also gives you the opportunity to engage with your clients on a higher level, providing insights and strategic recommendations for their businesses.